CSC 520 Artificial Intelligence I 
Introduction and overview of artificial intelligence. Elements of AI problemsolving techniques. State spaces and search techniques, including heuristic search (hillclimbing and A*). Logic (firstorder predicate calculus) and theorem proving (unification, resolution theorem proving). Advanced topics in machine learning, reasoning under uncertainty (Bayesian reasoning), and natural language processing as time permits. 3 credit hours. 

• Prerequisite  

Undergraduate degree in computer science with courses in data structures (CSC 316) AND applied discrete mathematics (CSC 226) or background in symbolic logic. Note: CSC 226 and 316 are offered as a part of the Computer Programming Certificate and can be taken online to fulfill this prerequisite. 

• Course Objectives  
CSC520 is the foundational artificial intelligence course. It is intended to prepare students for advanced courses in AI. A student successfully completing this course will be able to: (1) Identify representations and methodologies useful in the development of computerbased systems which exhibit aspects of intelligent behavior; (2) Program simple intelligent agents to operate in simple environments; (3) Identify the utility and limitations of knowledge representation methodologies such as propositional and predicate logic, rulebased systems, and probabilistic systems; (4) Identify the utility and limitations of companion reasoning methods, including resolution, rule processing, probabilistic reasoning, machine learning, and natural language processing; (5) Distinguish various uninformed and informed search algorithms and identify when each is appropriate; (6) Design and implement a series of simple intelligent agents of increasing complexity. 

• Course Requirements  
HOMEWORK: Programming Assignments (23), Other (12) 

• Textbook  
Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd Edition , Prentice Hall, 2010, ISBN 978013604259. 

• Computer and Internet Requirements  
NCSU and Engineering Online have recommended minimum specifications for computers. For details, click here. 

• Instructor  
Dr. Dennis R. Bahler, Associate Professor 
Phone: 9195153369

